scholarly journals Testing for dependence on tree structures

2019 ◽  
Author(s):  
Merle Behr ◽  
M. Azim Ansari ◽  
Axel Munk ◽  
Chris Holmes
Keyword(s):  
High Power ◽  
False Positive ◽  
Phylogenetic Trees ◽  
Ad Hoc ◽  
Group Structure ◽  
False Positive Rate ◽  
Biomedical Sciences ◽  
False Positive Error ◽  
Tree Structures ◽  
Response Variable

Tree structures, showing hierarchical relationships and the latent structures between samples, are ubiquitous in genomic and biomedical sciences. A common question in many studies is whether there is an association between a response variable measured on each sample and the latent group structure represented by some given tree. Currently this is addressed on an ad hoc basis, usually requiring the user to decide on an appropriate number of clusters to prune out of the tree to be tested against the response variable. Here we present a statistical method with statistical guarantees that tests for association between the response variable and a fixed tree structure across all levels of the tree hierarchy with high power, while accounting for the overall false positive error rate. This enhances the robustness and reproducibility of such findings.Significance StatementTree like structures are abundant in the empirical sciences as they can summarize high dimensional data and show latent structure among many samples in a single framework. Prominent examples include phylogenetic trees or hierarchical clustering derived from genetic data. Currently users employ ad hoc methods to test for association between a given tree and a response variable, which reduces reproducibility and robustness. In this paper, we introduce treeSeg, a simple to use and widely applicable methodology with high power for testing between all levels of hierarchy for a given tree and the response while accounting for the overall false positive rate. Our method allows for precise uncertainty quantification and therefore increases interpretability and reproducibility of such studies across many fields of science.

scholarly journals Testing for dependence on tree structures

2020 ◽  
Vol 117 (18) ◽  
pp. 9787-9792 ◽  
Author(s):  
Merle Behr ◽  
M. Azim Ansari ◽  
Axel Munk ◽  
Chris Holmes
Keyword(s):  
Ad Hoc ◽  
Group Structure ◽  
Biomedical Sciences ◽  
False Positive Error ◽  
Tree Structures ◽  
Response Variable ◽  
False Positive Error Rate ◽  
Latent Structures ◽  
Latent Group ◽  
Fixed Tree

Tree structures, showing hierarchical relationships and the latent structures between samples, are ubiquitous in genomic and biomedical sciences. A common question in many studies is whether there is an association between a response variable measured on each sample and the latent group structure represented by some given tree. Currently, this is addressed on an ad hoc basis, usually requiring the user to decide on an appropriate number of clusters to prune out of the tree to be tested against the response variable. Here, we present a statistical method with statistical guarantees that tests for association between the response variable and a fixed tree structure across all levels of the tree hierarchy with high power while accounting for the overall false positive error rate. This enhances the robustness and reproducibility of such findings.

Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
Author(s):  
S. Shung-Shung ◽  
S. Yu-Chien ◽  
Y. Mei-Due ◽  
W. Hwei-Chung ◽  
A. Kao
Keyword(s):  
Acute Appendicitis ◽  
False Positive ◽  
False Positive Rate ◽  
Accurate Method ◽  
Clinical Findings ◽  
Pathological Findings ◽  
Lower Quadrant ◽  
Predictive Values ◽  
Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

Predicting Fetal Chromosome Anomalies in the First Trimester Using Pregnancy Associated Plasma Protein-A: A Comparison of Statistical Methods

1993 ◽  
Vol 32 (02) ◽  
pp. 175-179 ◽  
Author(s):  
B. Brambati ◽  
T. Chard ◽  
J. G. Grudzinskas ◽  
M. C. M. Macintosh
Keyword(s):  
Logistic Regression ◽  
General Population ◽  
Likelihood Ratio ◽  
False Positive ◽  
False Positive Rate ◽  
Ratio Method ◽  
Detection Rates ◽  
Gaussian Distributions ◽  
Positive Rate ◽  
Likelihood Ratio Method

Abstract:The analysis of the clinical efficiency of a biochemical parameter in the prediction of chromosome anomalies is described, using a database of 475 cases including 30 abnormalities. A comparison was made of two different approaches to the statistical analysis: the use of Gaussian frequency distributions and likelihood ratios, and logistic regression. Both methods computed that for a 5% false-positive rate approximately 60% of anomalies are detected on the basis of maternal age and serum PAPP-A. The logistic regression analysis is appropriate where the outcome variable (chromosome anomaly) is binary and the detection rates refer to the original data only. The likelihood ratio method is used to predict the outcome in the general population. The latter method depends on the data or some transformation of the data fitting a known frequency distribution (Gaussian in this case). The precision of the predicted detection rates is limited by the small sample of abnormals (30 cases). Varying the means and standard deviations (to the limits of their 95% confidence intervals) of the fitted log Gaussian distributions resulted in a detection rate varying between 42% and 79% for a 5% false-positive rate. Thus, although the likelihood ratio method is potentially the better method in determining the usefulness of a test in the general population, larger numbers of abnormal cases are required to stabilise the means and standard deviations of the fitted log Gaussian distributions.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

Forensic science evidence: Naive estimates of false positive error rates and reliability

2020 ◽  
Author(s):  
Kristy Martire ◽  
Agnes Bali ◽  
Kaye Ballantyne ◽  
Gary Edmond ◽  
Richard Kemp ◽  
...  
Keyword(s):  
Forensic Science ◽  
False Positive ◽  
Error Rates ◽  
Forensic Sciences ◽  
Positive Error ◽  
False Positive Error ◽  
Reliability Estimates ◽  
Positive Report ◽  
Science Evidence ◽  
Science Disciplines

We do not know how often false positive reports are made in a range of forensic science disciplines. In the absence of this information it is important to understand the naive beliefs held by potential jurors about forensic science evidence reliability. It is these beliefs that will shape evaluations at trial. This descriptive study adds to our knowledge about naive beliefs by: 1) measuring jury-eligible (lay) perceptions of reliability for the largest range of forensic science disciplines to date, over three waves of data collection between 2011 and 2016 (n = 674); 2) calibrating reliability ratings with false positive report estimates; and 3) comparing lay reliability estimates with those of an opportunity sample of forensic practitioners (n = 53). Overall the data suggest that both jury-eligible participants and practitioners consider forensic evidence highly reliable. When compared to best or plausible estimates of reliability and error in the forensic sciences these views appear to overestimate reliability and underestimate the frequency of false positive errors. This result highlights the importance of collecting and disseminating empirically derived estimates of false positive error rates to ensure that practitioners and potential jurors have a realistic impression of the value of forensic science evidence.

Characteristics of false-positive alerts on transcranial motor evoked potential monitoring during pediatric scoliosis and adult spinal deformity surgery: an “anesthetic fade” phenomenon

2020 ◽  
Vol 32 (3) ◽  
pp. 423-431 ◽  
Author(s):  
Hiroki Ushirozako ◽  
Go Yoshida ◽  
Tomohiko Hasegawa ◽  
Yu Yamato ◽  
Tatsuya Yasuda ◽  
...  
Keyword(s):  
Spinal Deformity ◽  
False Positive ◽  
Adult Spinal Deformity ◽  
False Positive Rate ◽  
Multivariate Logistic Regression Analysis ◽  
Motor Evoked Potential ◽  
Scoliosis Surgery ◽  
True Negative ◽  
Duration Of Surgery ◽  
Spinal Deformity Surgery

OBJECTIVETranscranial motor evoked potential (TcMEP) monitoring may be valuable for predicting postoperative neurological complications with a high sensitivity and specificity, but one of the most frequent problems is the high false-positive rate. The purpose of this study was to clarify the differences in the risk factors for false-positive TcMEP alerts seen when performing surgery in patients with pediatric scoliosis and adult spinal deformity and to identify a method to reduce the false-positive rate.METHODSThe authors retrospectively analyzed 393 patients (282 adult and 111 pediatric patients) who underwent TcMEP monitoring while under total intravenous anesthesia during spinal deformity surgery. They defined their cutoff (alert) point as a final TcMEP amplitude of ≤ 30% of the baseline amplitude. Patients with false-positive alerts were classified into one of two groups: a group with pediatric scoliosis and a group with adult spinal deformity.RESULTSThere were 14 cases of false-positive alerts (13%) during pediatric scoliosis surgery and 62 cases of false-positive alerts (22%) during adult spinal deformity surgery. Compared to the true-negative cases during adult spinal deformity surgery, the false-positive cases had a significantly longer duration of surgery and greater estimated blood loss (both p < 0.001). Compared to the true-negative cases during pediatric scoliosis surgery, the false-positive cases had received a significantly higher total fentanyl dose and a higher mean propofol dose (0.75 ± 0.32 mg vs 0.51 ± 0.18 mg [p = 0.014] and 5.6 ± 0.8 mg/kg/hr vs 5.0 ± 0.7 mg/kg/hr [p = 0.009], respectively). A multivariate logistic regression analysis revealed that the duration of surgery (1-hour difference: OR 1.701; 95% CI 1.364–2.120; p < 0.001) was independently associated with false-positive alerts during adult spinal deformity surgery. A multivariate logistic regression analysis revealed that the mean propofol dose (1-mg/kg/hr difference: OR 3.117; 95% CI 1.196–8.123; p = 0.020), the total fentanyl dose (0.05-mg difference; OR 1.270; 95% CI 1.078–1.497; p = 0.004), and the duration of surgery (1-hour difference: OR 2.685; 95% CI 1.131–6.377; p = 0.025) were independently associated with false-positive alerts during pediatric scoliosis surgery.CONCLUSIONSLonger duration of surgery and greater blood loss are more likely to result in false-positive alerts during adult spinal deformity surgery. In particular, anesthetic doses were associated with false-positive TcMEP alerts during pediatric scoliosis surgery. The authors believe that false-positive alerts during pediatric scoliosis surgery, in particular, are caused by “anesthetic fade.”

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

Evidence for Age-Adjusted D-Dimer to Rule out Pulmonary Embolism: An Institutional Study

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S5-S5
Author(s):  
Ridin Balakrishnan ◽  
Daniel Casa ◽  
Morayma Reyes Gil
Keyword(s):  
Pulmonary Embolism ◽  
False Positive ◽  
False Positive Rate ◽  
Moderate Risk ◽  
Older Population ◽  
Statistical Measures ◽  
Positive Rate ◽  
Risk Patients ◽  
D Dimer ◽  
Rule Out

Abstract The diagnostic approach for ruling out suspected acute pulmonary embolism (PE) in the ED setting includes several tests: ultrasound, plasma d-dimer assays, ventilation-perfusion scans and computed tomography pulmonary angiography (CTPA). Importantly, a pretest probability scoring algorithm is highly recommended to triage high risk cases while also preventing unnecessary testing and harm to low/moderate risk patients. The d-dimer assay (both ELISA and immunoturbidometric) has been shown to be extremely sensitive to rule out PE in conjunction with clinical probability. In particularly, d-dimer testing is recommended for low/moderate risk patients, in whom a negative d-dimer essentially rules out PE sparing these patients from CTPA radiation exposure, longer hospital stay and anticoagulation. However, an unspecific increase in fibrin-degradation related products has been seen with increase in age, resulting in higher false positive rate in the older population. This study analyzed patient visits to the ED of a large academic institution for five years and looked at the relationship between d-dimer values, age and CTPA results to better understand the value of age-adjusted d-dimer cut-offs in ruling out PE in the older population. A total of 7660 ED visits had a CTPA done to rule out PE; out of which 1875 cases had a d-dimer done in conjunction with the CT and 5875 had only CTPA done. Out of the 1875 cases, 1591 had positive d-dimer results (&gt;0.50 µg/ml (FEU)), of which 910 (57%) were from patients older than or equal to fifty years of age. In these older patients, 779 (86%) had a negative CT result. The following were the statistical measures of the d-dimer test before adjusting for age: sensitivity (98%), specificity (12%); negative predictive value (98%) and false positive rate (88%). After adjusting for age in people older than 50 years (d-dimer cut off = age/100), 138 patients eventually turned out to be d-dimer negative and every case but four had a CT result that was also negative for a PE. The four cases included two non-diagnostic results and two with subacute/chronic/subsegmental PE on imaging. None of these four patients were prescribed anticoagulation. The statistical measures of the d-dimer test after adjusting for age showed: sensitivity (96%), specificity (20%); negative predictive value (98%) and a decrease in the false positive rate (80%). Therefore, imaging could have been potentially avoided in 138/779 (18%) of the patients who were part of this older population and had eventual negative or not clinically significant findings on CTPA if age-adjusted d-dimers were used. This data very strongly advocates for the clinical usefulness of an age-adjusted cut-off of d-dimer to rule out PE.

scholarly journals Mitigation of biases in estimating hazard ratios under non-sensitive and non-specific observation of outcomes–applications to influenza vaccine effectiveness

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Ulrike Baum ◽  
Sangita Kulathinal ◽  
Kari Auranen
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Vaccine Effectiveness ◽  
Partial Likelihood ◽  
Event Data ◽  
Time To Event ◽  
Positive Events ◽  
Time To Event Data ◽  
Hazard Ratios ◽  
Positive Rate

Abstract Background Non-sensitive and non-specific observation of outcomes in time-to-event data affects event counts as well as the risk sets, thus, biasing the estimation of hazard ratios. We investigate how imperfect observation of incident events affects the estimation of vaccine effectiveness based on hazard ratios. Methods Imperfect time-to-event data contain two classes of events: a portion of the true events of interest; and false-positive events mistakenly recorded as events of interest. We develop an estimation method utilising a weighted partial likelihood and probabilistic deletion of false-positive events and assuming the sensitivity and the false-positive rate are known. The performance of the method is evaluated using simulated and Finnish register data. Results The novel method enables unbiased semiparametric estimation of hazard ratios from imperfect time-to-event data. False-positive rates that are small can be approximated to be zero without inducing bias. The method is robust to misspecification of the sensitivity as long as the ratio of the sensitivity in the vaccinated and the unvaccinated is specified correctly and the cumulative risk of the true event is small. Conclusions The weighted partial likelihood can be used to adjust for outcome measurement errors in the estimation of hazard ratios and effectiveness but requires specifying the sensitivity and the false-positive rate. In absence of exact information about these parameters, the method works as a tool for assessing the potential magnitude of bias given a range of likely parameter values.

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